Center for Genomics and Personalized Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.
J Allergy Clin Immunol. 2013 Jul;132(1):72-80. doi: 10.1016/j.jaci.2013.03.044. Epub 2013 May 21.
Sputum eosinophil percentages are a strong predictor of airway inflammation and exacerbations and aid asthma management, whereas sputum neutrophil percentages indicate a different severe asthma phenotype that is potentially less responsive to TH2-targeted therapy. Variables, such as blood eosinophil counts, total IgE levels, fraction of exhaled nitric oxide (Feno) levels, or FEV1 percent predicted, might predict airway eosinophil percentages, whereas age, FEV1 percent predicted, or blood neutrophil counts might predict sputum neutrophil percentages. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway eosinophil and neutrophil percentages either individually or combined is not established.
We sought to determine whether blood eosinophil counts, Feno levels, and IgE levels accurately predict sputum eosinophil percentages and whether age, FEV1 percent predicted, and blood neutrophil counts accurately predict sputum neutrophil percentages.
Subjects in the Wake Forest Severe Asthma Research Program (n = 328) were characterized by blood and sputum cell counts, health care use, lung function, Feno levels, and IgE levels. Multiple analytic techniques were used.
Despite significant association with sputum eosinophil percentages, blood eosinophil counts, Feno levels, and total IgE levels did not accurately predict sputum eosinophil percentages, and combinations of these variables did not improve prediction. Age, FEV1 percent predicted, and blood neutrophil counts were similarly unsatisfactory for the prediction of sputum neutrophil percentages. Factor analysis and stepwise selection found Feno levels, IgE levels, and FEV1 percent predicted, but not blood eosinophil counts, correctly predicted 69% of sputum eosinophil percentages of less than 2% or 2% and greater. Likewise, age, asthma duration, and blood neutrophil counts correctly predicted 64% of sputum neutrophil percentages of less than 40% or 40% and greater. A model to predict both sputum eosinophil and neutrophil percentages accurately assigned only 41% of samples.
Despite statistically significant associations, Feno levels, IgE levels, blood eosinophil and neutrophil counts, FEV1 percent predicted, and age are poor surrogates, both separately and combined, for accurately predicting sputum eosinophil and neutrophil percentages.
痰嗜酸性粒细胞百分比是气道炎症和加重的强有力预测因子,并有助于哮喘管理,而痰中性粒细胞百分比则表明一种不同的严重哮喘表型,其对 TH2 靶向治疗的反应可能较差。一些变量,如血液嗜酸性粒细胞计数、总 IgE 水平、呼气一氧化氮分数(Feno)水平或 FEV1 预计百分比,可能预测气道嗜酸性粒细胞百分比,而年龄、FEV1 预计百分比或血液中性粒细胞计数可能预测痰中性粒细胞百分比。可用性和测量的便利性是有用的特征,但单独或联合预测气道嗜酸性粒细胞和中性粒细胞百分比的准确性尚未确定。
我们旨在确定血液嗜酸性粒细胞计数、Feno 水平和 IgE 水平是否能准确预测痰嗜酸性粒细胞百分比,以及年龄、FEV1 预计百分比和血液中性粒细胞计数是否能准确预测痰中性粒细胞百分比。
温斯顿-塞勒姆维克森林严重哮喘研究计划(Wake Forest Severe Asthma Research Program,WFSARP)中的受试者通过血液和痰细胞计数、医疗保健使用、肺功能、Feno 水平和 IgE 水平进行特征描述。使用了多种分析技术。
尽管与痰嗜酸性粒细胞百分比有显著关联,但血液嗜酸性粒细胞计数、Feno 水平和总 IgE 水平并不能准确预测痰嗜酸性粒细胞百分比,这些变量的组合也不能改善预测。年龄、FEV1 预计百分比和血液中性粒细胞计数同样不能准确预测痰中性粒细胞百分比。因子分析和逐步选择发现,Feno 水平、IgE 水平和 FEV1 预计百分比,但不是血液嗜酸性粒细胞计数,正确预测了小于 2%或 2%及以上的痰嗜酸性粒细胞百分比的 69%。同样,年龄、哮喘持续时间和血液中性粒细胞计数正确预测了小于 40%或 40%及以上的痰中性粒细胞百分比的 64%。一个能够准确预测痰嗜酸性粒细胞和中性粒细胞百分比的模型,仅将 41%的样本分类正确。
尽管存在统计学上的显著关联,但 Feno 水平、IgE 水平、血液嗜酸性粒细胞和中性粒细胞计数、FEV1 预计百分比和年龄,无论是单独使用还是联合使用,都是准确预测痰嗜酸性粒细胞和中性粒细胞百分比的较差替代指标。